Interview with Norbert Dolle, Co-founder & Managing Partner at White Space Energy
There’s so much innovation happening in the oil & gas sector. Before we dig into your outlook on the sector and what’s on the horizon, tell us how you got involved in the industry and some more about White Space Energy.
White Space’s roots are in the industry. All founders of the company worked with Shell for up to two decades, and that is also where our strong belief stems from – that we can collectively do much better when it comes to making complex decisions.
We also realised that true innovation requires a certain mental freedom, or white space – so we founded White Space Energy in 2019. We support organisations in making radically better business decisions using AI as an assistant, and so far we have been very privileged in working with and sharing this mission with some of the major players in our industry.
What’s your short-term outlook on the oil & gas industry?
The industry will continue to face increasing pressure from society, regulators and investors to transition towards a lower carbon or carbon neutral future. Yet, in the medium term the world still relies heavily on hydrocarbons and derivative products. Countries and regions will transition at a different pace, while climate issues can only be tackled through global collaboration.
I think that we have to be careful for knee-jerk decisions that do more harm than good, but that is more driven by politics. Our industry simply needs to be leading the change and demonstrate that it can reduce or offset emissions and produce lower carbon products. The world demands that, hence that change is our social license to continue to operate.
What do you think the shape of post-pandemic recovery looks like for Asia and other regions across the world?
That’s not really my area of expertise, but I’m an optimist and think that economic recovery will be quick! Demand will most likely bounce back to at least pre-pandemic levels and countries will be once again be looking for growth. However, the pace of energy transition may initially be somewhat slower in Asia as compared to Europe.
Combined with post-pandemic economic growth that offers opportunities for the industry, it also poses a risk that regional oil and gas players may not yet feel the urgency to become more sustainable.
What role will vertical integration between downstream, midstream and upstream play in the next normal of the oil and gas downstream industry, and how does that link into digital transformation?
To remain competitive, companies will continue to look for sustainability, efficiency and value improvements across the entire value chain. So it is likely that the industry will further strengthen collaboration – and possibly integration – between down-, mid- and upstream. Digital solutions that are based on applications of blockchain, advanced analytics and AI will enable these improvements.
I think that we will also see a stronger collaboration, or partnering, between operating companies and (digital) service providers to truly transform the industry.
How important is culture when implementing AI into the business infrastructure? And what can business leaders do to ensure that AI is accessible and understood across all parts of the business?
Culture is so important! Organizations cannot change without a culture of innovation and risk-taking. In a digital transformation journey there will always be things that go wrong. Instead of penalizing those, business leaders should take those as opportunities to learn and improve. We often see that middle management is not incentivised to take risks. The workforce would love to try out new technologies, but their managers feel exposed. Leaders need to create that safe environment in which experimentation can lead to innovation and change.
When it comes to accessible and understandable AI, it again comes down to user-centricity. Work with end users throughout the organization when designing and implementing AI solutions. Change management is often underestimated. So my advice is to spend enough time with users to build trust in the digital solution, and work with solution providers that are willing to provide that transparency.
As digital technologies are increasingly introduced into operations, in what way will they improve energy sustainability?
Operational excellence is one of the key pillars for energy sustainability in existing assets. So that means things like maintaining the equipment such that there are no process upsets, minimizing energy usage in the process, maximizing the use of available workforce and resources.
Digital technologies can support operational excellence in two areas: monitoring & optimization. Making plant performance visible, in real time, to operators and management is a first step towards optimizing the operations. Digital solutions for predictive maintenance can then be used to become more pro-active in operating the plant. And finally, there is more advanced optimization techniques (such as AI) that can be used to maximize process performance and resource utilization.
Operational excellence improves energy sustainability; it is also simply good business. We recently worked with an upstream operator on maintenance and logistics planning. Optimizing their plans by using AI resulted in 20% lower helicopter flying hours. That is 20% lower emissions, but also 20% lower operating cost.
Interestingly, our clients have been asking more and more to include CO2 metrics into our AI assisted decision-making solutions. So the industry is definitely changing, and changing quite fast.
Finally, tell us more about your presentation at this year’s Asian Downstream Summit virtual conference.
We will present an interesting use case in which we applied AI to optimize maintenance planning in a biorefinery in Norway. A custom digital solution was developed to support the planning team in using the algorithms to evaluate different planning scenarios and to write the results back to the maintenance management system. Business results to-date indicate more than 30% higher resource utilization, which is a step change improvement in efficiency, and resulting reliability and safety of the plant. We often hear operators talking about poor data quality as a reason to not yet start with optimization. Interestingly, in this use case the introduction of optimization not only resulted in better business results, but also triggered improvements in work processes and data management.